习题10.1

合集 - python数学建模课后习题(41)

1.习题5.4求解非凸非线性规划2024-10-112.习题5.5求非凸函数的线性规划问题2024-10-123.习题6.42024-10-144.习题6.32024-10-145.习题6.22024-10-146.习题5.7 生产计划问题2024-10-147.习题4.3 求4.3节模型二的解2024-10-158.习题2.12024-10-159.习题2.22024-10-1510.习题2.32024-10-1511.习题2.42024-10-1512.习题2.5（1）2024-10-1513.习题2.5（2）2024-10-1514.习题2.62024-10-1515.习题2.7（1）2024-10-1516.习题2.7（2）2024-10-1517.习题2.82024-10-1518.习题2.92024-10-1519.习题2.102024-10-1520.习题2.112024-10-1521.习题2.122024-10-1522.习题2.132024-10-1523.习题3.22024-10-1524.习题3.32024-10-1525.习题6.52024-10-2626.习题6.62024-10-2627.习题7.12024-11-1228.习题7.32024-11-1229.习题7.42024-11-1230.习题7.72024-11-1231.习题7.102024-11-1232.习题8.42024-11-1233.习题8.52024-11-1234.8.8最优捕鱼策略2024-12-0935.8.92024-12-0936.9.2车间生产滚珠2024-12-0937.9.32024-12-0938.9.52024-12-09

39.习题10.12024-12-21

40.习题10.22024-12-2141.习题10.32024-12-21

收起

import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt

def check(data):
    # 提取数据的第一列和第二列
    x = data[:, 0]
    y = data[:, 1]
    # 使用statsmodels进行线性回归分析
    model = sm.OLS(y, sm.add_constant(x)).fit()  # 添加常数项
    print(model.summary())
    print(model.outlier_test())  # 输出已知数据的野值检验
    print('残差的方差', model.mse_resid)
    # 获取预测结果
    predictions = model.get_prediction(data).summary_frame(alpha=0.05)
    lower, upper = predictions.conf_int[1].T  # 置信下限上限
    error_bars = (upper - lower) / 2  # 置信半径
    num = np.arange(1, len(x) + 1)
    plt.errorbar(num, model.resid, error_bars, fmt='o')
    plt.show()

# 加载数据，确保路径正确
data_path = r'C:\Users\fangz\Desktop\python course\练习题目\第10章\data10_1.txt'
a = np.loadtxt(data_path)
plt.rc('font', size=15)  # 设置字体大小
plt.plot(a[:, 0], a[:, 1], 'o')  # 绘制原始数据点
plt.figure()  # 创建新图形
check(a)  # 执行回归分析

# 删除第9列数据
a2 = np.delete(a, 8, axis=1)
check(a2)

# 删除第5列数据
a3 = np.delete(a, 4, axis=1)
check(a3)

print("学号后两位：08")

结果如下图所示：